Distinction between harmonic and structural components in ambient excitation tests using the time–frequency domain decomposition technique

The time–frequency domain decomposition technique has been proposed for modal identification in ambient vibration testing. In the presence of harmonic excitations, the modal identification process can provide not only structural modes but also non-structural ones relative to harmonic components. It is thus important to distinguish between them. In this study, by using the time–frequency domain decomposition technique, it is demonstrated that the distinction between non-structural harmonic components and those of the structural responses can be possible, and it is merged into the general procedure of the time–frequency domain decomposition method. This proposition is then verified by numerical examples and by a laboratory test.

[1]  Filipe Magalhães,et al.  Damping Estimation Using Free Decays and Ambient Vibration Tests , 2010 .

[2]  J. Antoni The spectral kurtosis: a useful tool for characterising non-stationary signals , 2006 .

[3]  J. Slavič,et al.  Damping identification using a continuous wavelet transform: application to real data , 2003 .

[4]  Gaël Chevallier,et al.  Tracking and removing modulated sinusoidal components: A solution based on the kurtosis and the Extended , 2013 .

[5]  W. Staszewski IDENTIFICATION OF DAMPING IN MDOF SYSTEMS USING TIME-SCALE DECOMPOSITION , 1997 .

[6]  Palle Andersen,et al.  Modal Identification from Ambient Responses using Frequency Domain Decomposition , 2000 .

[7]  Bruno Torrésani,et al.  Practical Time-Frequency Analysis , 1998 .

[8]  Gaël Chevallier,et al.  Harmonic component detection: Optimized Spectral Kurtosis for operational modal analysis , 2012 .

[9]  T. Le,et al.  Continuous wavelet transform for modal identification using free decay response , 2004 .

[10]  Palle Andersen,et al.  An Indicator for Separation of Structural and Harmonic Modes in Output-Only Modal Testing , 2000 .

[11]  P. Paultre,et al.  Modal identification based on the time–frequency domain decomposition of unknown-input dynamic tests , 2013 .

[12]  T. T. Soong,et al.  Fundamentals of Probability and Statistics for Engineers , 2004 .

[13]  Filipe Magalhães,et al.  Ambient vibration re-testing and operational modal analysis of the Humber Bridge , 2010 .

[14]  Bruno Torrésani,et al.  Practical Time-Frequency Analysis, Volume 9: Gabor and Wavelet Transforms, with an Implementation in S , 1998 .

[15]  Carlos E. Ventura,et al.  Damping estimation by frequency domain decomposition , 2001 .

[16]  Mahir Ülker-Kaustell,et al.  Application of the continuous wavelet transform on the free vibrations of a steel–concrete composite railway bridge , 2011 .

[17]  Nuno M. M. Maia,et al.  Theoretical and Experimental Modal Analysis , 1997 .

[18]  B. Peeters,et al.  Stochastic System Identification for Operational Modal Analysis: A Review , 2001 .

[19]  Palle Andersen,et al.  Estimating Modal Parameters of Civil Engineering Structures subject to Ambient and Harmonic Excitation , 2007 .

[20]  Joseph Lardies,et al.  Identification of modal parameters using the wavelet transform , 2002 .

[21]  J. Antoni Blind separation of vibration components: Principles and demonstrations , 2005 .

[22]  Jean-Claude Golinval,et al.  Application of ARMAV models to the identification and damage detection of mechanical and civil engineering structures , 2001 .

[23]  Christof Devriendt,et al.  Operational modal analysis in the presence of harmonic excitations by the use of transmissibility measurements , 2009 .

[24]  Massimo Ruzzene,et al.  NATURAL FREQUENCIES AND DAMPINGS IDENTIFICATION USING WAVELET TRANSFORM: APPLICATION TO REAL DATA , 1997 .

[25]  Patrick Paultre,et al.  Modal identification based on continuous wavelet transform and ambient excitation tests , 2012 .